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Innovation and digital transformation in local communities
No full textThe use of technology is inevitable in a society of knowledge, being implemented including at the level of local governments where has the potential to improve interactions between local authorities and citizens through the simplification of procedures, as well as contributing to open local government. The innovation and digital transformation of government means the further modernisation of public administration, seamless cross-border mobility and enhanced digital interactions. The paper aim is to show that local governments operate in an increasingly open and receptive manner by using innovation and an increasing number of digital tools that facilitate the development of local communities and the improvement of living standards
Guest Editorial - Curry clubs, uncertain times, and social media
No full textCOVID-19, the eternal hospital winter, heatwaves, global warming, energy costs, inflation, and an unnecessary war. We truly do live in uncertain times. That said, we would wager our grandparents said the same thing. What gets us through is family, friends and out shared communities, including acute medicine. Which brings us to this edition of the journal, where many excellent articles will hopefully distract our reader from all the doom and gloom, and instead light up your grey cells
Robotics cyber security issues
No full textRobotics is becoming more ubiquitous, and this technology has existed for almost a century and also keeps continuously evolving with better capabilities and advancements in an environment which includes both hardware and software. Nowadays, Robotics come in different shapes with different capabilities. These days, a robot can be small, and simple and still have increased performance and productivity. Additionally, this technology has become an essential component of daily life, and robotics automation usage cases have expanded from household utilities to medical, or space projects, defense, and education. Robotic functionalities are similar to computer systems running by a program that is defined to repeat tasks or operations. Moreover, they experience security problems that are comparable to those that computer systems have had for years. Hence, when robots are compromised, it immediately affects two different areas.: I. Physical elements may raise concern in three key aspects; integrity, confidentiality, and availability of the robot system’s operations and functions. It can also lead to attacks or hacks. I. Virtual security vulnerabilities can be found in provider platforms, misconfigurations, built-in weaknesses in robot systems, and risks in data communications channels. For instance, the WIFI connection may be designed with a poor encryption system. Therefore, both physical and virtual problems in robotics systems are part of cybersecurity in Robotics which is rapidly growing. In this case, the paper focuses on cybersecurity in Robotics and identifies security gaps, vulnerabilities, and risks
“You can end up in a happy place” (Voyce): A role for positive autoethnography”
No full textThe purpose of this opinion piece is to present a case for the potential of positive autoethnography as a new autoethnographic approach.This work resulted from on-going discussions between the authors as to the practicalities and benefits of associating the qualitative approach of autoethnography with the field of positive psychology.Positive autoethnography (PosAE) is proposed to encourage writers to actively reflect on the importance for themselves, and their readers, of including positive narrative elements, prospective visions and exploratory trajectories in their work.This research builds on existing research that has included positive psychology in autoethnography. As positive psychology is grounded in empirical research, we are suggesting that PosAE is allied to pragmatic autoethnography (PAE).Positive autoethnography offers to facilitate positive thought, affect and strategies that could improve well-being. For example, some people struggling with serious health issues, and those helping them, may find it useful for articulating conditions and envisioning, even experiencing, positive change.With so many lives impacted by mental health issues globally, and with rapidly changing societies struggling to provide stability and purpose, an autoethnography that provides discursive tools such as PERMA (Positive emotions, Engagement, Positive Relationships, Meaning, Accomplishments/Achievements) to communicate the positive seems timely.This is the first time the creation of an autoethnographic approach explicitly linked to positive psychology has been proposed
Stars in the making : the rise of UK migrant entrepreneurs
No full textThe UK used to be primarily an emigration country, but in recent years, far more migrants have arrived at the UK borders. These immigrants play a vital role in the country's entrepreneurial landscape, with many starting businesses contributing to the economy's growth and development. Migrant entrepreneurs are essential to the UK's entrepreneurial ecosystem, contributing to economic growth and job creation. However, starting and running a business in a new country can be challenging, particularly for migrants who face cultural, language, and regulatory barriers. Therefore, to thrive as a migrant entrepreneur in the UK, specific skills are necessary. This paper examines the experiences of Nigerian immigrant entrepreneurs in the UK, focusing on identifying challenges, opportunities and critical entrepreneurship skills immigrant entrepreneurs need to succeed in the UK business landscape
E-commerce website usability analysis using the association rule mining and machine learning algorithm
No full textThe overall effectiveness of a website as an e-commerce platform is influenced by how usable it is. This study aimed to find out if advanced web metrics, derived from Google Analytics software, could be used to evaluate the overall usability of e-commerce sites and identify potential usability issues. It is simple to gather web indicators, but processing and interpretation take time. This data is produced through several digital channels, including mobile. Big data has proven to be very helpful in a variety of online platforms, including social networking and e-commerce websites, etc. The sheer amount of data that needs to be processed and assessed to be useful is one of the main issues with e-commerce today as a result of the digital revolution. Additionally, on social media a crucial growth strategy for e-commerce is the usage of BDA capabilities as a guideline to boost sales and draw clients for suppliers. In this paper, we have used the KMP algorithm-based multivariate pruning method for web-based web index searching and different web analytics algorithm with machine learning classifiers to achieve patterns from transactional data gathered from e-commerce websites. Moreover, through the use of log-based transactional data, the research presented in this paper suggests a new machine learning-based evaluation method for evaluating the usability of e-commerce websites. To identify the underlying relationship between the overall usability of the eLearning system and its predictor factors, three machine learning techniques and multiple linear regressions are used to create prediction models. This strategy will lead the e-commerce industry to an economically profitable stage. This capability can assist a vendor in keeping track of customers and items they have viewed, as well as categorizing how customers use their e-commerce emporium so the vendor can cater to their specific needs. It has been proposed that machine learning models, by offering trustworthy prognoses, can aid in excellent usability. Such models might be incorporated into an online prognostic calculator or tool to help with treatment selection and possibly increase visibility. However, none of these models have been recommended for use in reusability because of concerns about the deployment of machine learning in e-commerce and technical issues. One problem with machine learning science that needs to be solved is explainability. For instance, let us say B is 10 and all the people in our population are even. The hash function’s behavior is not random since only buckets 0, 2, 4, 6, and 8 can be the value of h(x). However, if B = 11, we would find that 1/11th of the even integers is transmitted to each of the 11 buckets. The hash function would work well in this situation
A critical analysis of Islamic financial literacy and Islamic financial inclusion of Thai Muslims in the five southernmost provinces of Thailand
No full textFinancial literacy is widely recognised as a way to improve quality access to financial services.Nonetheless, the study of Islamic financial literacy can be viewed as a novel concept, particularly in a Muslim minority country. Moreover, research that examines financial literacy and inclusion from an Islamic perspective is still limited. Considering these factors, this study aims to critically assess Islamic financial literacy and inclusion in Thailand's five southernmost provinces as well as identify the means to enhance them. After reviewing the relevant literature, a conceptual framework for Islamic financial literacy, indicators of Islamic financial inclusion, and an extended theory of planned behaviour model were developed to address the research questions. Based on mixed methods research design, a questionnaire and semi-structured interviews were employed to collect quantitative and qualitative data. Then, the obtained data were analysed using descriptive statistics, structural equation modelling, and thematic analysis.The questionnaire and interview results indicate that most Muslims in the area were unaware of Islamic financial products and excluded from Islamic financial services. Then, the analysis of structural equation modelling demonstrates that the integration of Islamic financial literacy as the salient behavioural belief had a significant impact on the attitude to adopt Islamic finance, except for the influence of Islamic money management. The analysis also shows that the predictors of the theory of planned behaviour model were significant determinants of the intention to adopt Islamic finance, despite the fact that attitude and intention had a significant negative relationship.In this regard, the interview data plays a crucial role in supporting the analysis by providing explanations for the influential factors. Drawing upon empirical evidence, the study has proposed proactive policy recommendations to enhance Islamic financial literacy and inclusion among the Muslim population, with the aim to promote a more inclusive and sustainable financial system to benefit the overall economy. Overall, the findings of this study make a valuable contribution to the body of knowledge in terms of contextual, theoretical, and methodological perspectives
Sustainable technology adoption as a source of competitive advantage for pineapple production in Ejigbo, Nigeria
No full textAdopting new technology as a strategic resource can result in a competitive edge in any market. However, a competitive advantage cannot be acquired in the production of horticultural goods without first embracing the practices that are inextricably linked to those goods. This paper investigates the adoption of farm practices in conjunction with technology transferred to farmers.Some research debates on competitive advantages have identified both resources and processes of production as sources of competitive advantage. The emphasis on the resource-based view and dynamic capability view stipulates that firms acquire competitiveness via internal resources and capabilities. However, there has not been much empirical exploration of horticultural production sustainability in this regard despite its sufficiently outstanding contribution to the gross domestic product in developing and developed economies. It specifically discusses how Technology Adoption Practices (TAP) could lead to a competitive advantage in horticulture with particular reference to the production of pineapple fruit in Ejigbo, Nigeria. From the angle of professional practice; the study provides an insight into how farmers strive to suggest solutions to practical challenges faced within the production process. Therefore, it is essential to have practices in place for the adoption of sustainable technology. The outcomes of the study generate two different storylines and demonstrate that attributing factors as well as reinforcing capabilities both boost competitiveness at the farm level and enhance the farmers’ desire for farming pineapples. Pineapple farmers in Ejigbo employ a differentiation approach to gain a competitive advantage in their agro-farming industry. This could lead to an increase in the volume of fresh pineapple products that are exporte
Carbonic acid gas emission rating by vehicles using datascience techniques
No full textOne factor contributing to the warming of the upper orbit is the rollout of man-made pollutants into the eco system (biogas, Dioxide, laughing gas, and so on). Approximately 14% of total worldwide carbon dioxide emissions are attributed to the road transport. Wheels dust are dangerous to us and contain global warm gases that leads to changes in climate. Products of gas and diesel fuels that include NO2, CO, CH, C6H6, CH2O. Wheels also emit CO2, common human-caused global warm gas. It has been set emission targets to dramatically reduce highway's contribution to Dioxide. These are inferred from the global weather conference's goal of keeping the peak warming of the planet to a maximum of 2 degrees Celsius until 2100. In order to accomplish, in this study, a machine learning hybrid algorithm was developed in the combination of many classifications’ algorithm to find the vehicle CO2 emission with high accuracy rate. The results show that hybrid models can produce more accuracy with a lower error rate when developing an application for emission rating. Accurate carbon emission prediction models can aid in the development of emission-reduction policies
An effective analysis of palm print detection using Resnet framework in comparison with Recurrent Neural Network to improve classification accuracy
No full textThe goal of the proposed study is to use ResNet rather than a novel recurrent neural network to identify plant diseases with greater classification accuracy. Materials and Methods: The detection of plant disease is performed using ResNet and Recurrent Neural Network algorithms. The sample size for each sample is considered as 10 which is performed with a G power calculator. Results: The ResNet algorithm exhibited better results with classification accuracy of 95% compared to that of Novel Recurrent Neural Network with accuracy of 85%. The insignificant accuracy value of p=0.139 (p>0.05) is attained through SPSS Statistical Analysis.Conclusion: The classification of plant disease using ResNet is better than the Novel Recurrent Neural Network